Driving Forces of Agricultural Land Abandonment: A Lithuanian Case

Daiva Juknelienė (), Viktorija Narmontienė, Jolanta Valčiukienė and Gintautas Mozgeris
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Daiva Juknelienė: Agriculture Academy, Vytautas Magnus University, Studentų Str. 11, Akademija, 53361 Kaunas, Lithuania
Viktorija Narmontienė: Agriculture Academy, Vytautas Magnus University, Studentų Str. 11, Akademija, 53361 Kaunas, Lithuania
Jolanta Valčiukienė: Agriculture Academy, Vytautas Magnus University, Studentų Str. 11, Akademija, 53361 Kaunas, Lithuania
Gintautas Mozgeris: Agriculture Academy, Vytautas Magnus University, Studentų Str. 11, Akademija, 53361 Kaunas, Lithuania

Land, 2025, vol. 14, issue 4, 1-23

Abstract: The abandonment of agricultural land is now considered one of the primary land use changes driven by complex interactions between social, economic, and environmental factors. To understand and manage this process, a holistic approach that integrates multidimensional methodologies and interactions is essential. This study examines the key driving factors behind agricultural land abandonment in Lithuania using two methodological approaches. First, seventeen highly qualified land management experts were surveyed, and their insights were analysed using in-depth qualitative interviews, focusing on agricultural land abandonment and its underlying factors. Second, the development of agricultural land abandonment in a representative Lithuanian municipality was modelled using Markov chain models, incorporating freely available geographic data as factors influencing land use transformation. Actual areas of abandoned agricultural land were mapped using orthophotos from 2012, 2018, and 2021, for both model development and validation. The importance of predictors in the model was then assessed in relation to their significance as drivers of agricultural land abandonment. The findings indicate that natural factors, such as the proximity of forests and topographical constraints, play a significant role in explaining land abandonment processes. Additionally, agricultural land abandonment is influenced by social, economic, and legal factors, including land ownership structures, migration, and infrastructure accessibility. The importance of soil quality, productivity, and the presence of nearby arable land was found to vary depending on data accuracy and local environmental conditions, highlighting the complexity of agricultural land use patterns. The chosen mixed-method approach, combining qualitative surveys with numerical spatial modelling, demonstrates potential for identifying critical land use areas and providing insights to improve land management policies and decision making.

Keywords: agricultural land abandonment; land use change; qualitative survey; spatial modelling; Markov chain model (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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